Radon modelling with time-frequency sparseness weights

A flexible Radon modelling algorithm using time-frequency sparseness weights is introduced. The method may be used for a number of applications and combines the dealiasing and time resolution benefits of existing methods. Compared with a frequency domain sparseness approach, the proposed method results in improved attenuation of low moveout multiples and better primary preservation. Demultiple results using a North Sea dataset are shown.